Hop eld Model of Associative Memory as a Test Function of Evolutionary Computations
نویسندگان
چکیده
We apply genetic algorithms to Hop eld's neural network model of associative memory. Previously, using ternary chromosomes, we successfully evolved both random weight matrix and over-loaded Hebbian weight matrix to function as an associative memory. In this paper, we present a real-encoded genetic algorithm to evolve random synaptic weights to store some number of patterns as associative memory. The goal is to study how can we use the Hop eld model as a test suite for evolutionary computations.
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